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At least 649 records · Page 36
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NASA NTRS1985

The global joule heat production rate and the AE index

The degree of accuracy with which the AE index may be used as a measure of the joule heat production rate is evaluated for a typical substorm event on March 18, 1978, by estimating the global joule heat production rate as a function of time on the basis of data obtained from the IMS's six meridian chains. It is found that, although the AE index is statistically linearly related to the global joule heat production rate, caution is required when one assumes that details of AE index time variations during individual events are representative of those of the joule heat production rate.

Wei, S.↗
NASA NTRS1986

Prospects for an orbital determination and capture cell experiment

A dust experiment which combines measurements of the elemental and isotopic composition of individual particles with orbital information would contribute fundamental, new scientific information on the sources contributing to the micrometeoroid population. The general boundary conditions for such a system are: (1) it must be capable of measuring velocities in the range of 10 km/sec to 100 km/sec with several percent accuracy; (2) it must collect particles in such a way that the debris atoms are locally concentrated so that precise isotopic measurements are possible; (3) it should collect particles over a wide range of sizes starting with a lower limit of 10 microns; (4) it should incorporate materials that will not compromise the isotopic measurements; and (5) it should be large enough to obtain statistically meaningful results within a reasonable exposure time. Techniques which may satisfy these conditions are described.

Carey, W. C.↗
NASA NTRS1987

Static aeroelastic effects on the flutter of a supercritical wing

The results of an effort to calculate the effects of angle of attack and the associated aeroelastic deformation on the flutter of a highly swept supercritical wing by use of the modified strip analysis employed in previous studies of this wing are discussed. The spanwise distributions of steady state section lift-curve slope and aerodynamic center required as input for these calculations were obtained from static aeroelastic calculations for the wing by use of the FLO22 transonic code and an assumed dynamic pressure. The process is iterative so that flutter can be obtained at the same dynamic pressure as that used to calculate the statistically deformed shape and loading about which the flutter oscillation occurs (matched conditions). The results of this investigation show that the unconventional backward turn of the transonic dip in the experimental flutter boundary for angles of attack greater than zero is caused by variations in mass ratio and not by static aeroelastic deformation, although inclusion of the latter appears to be required for quantitative accuracy in the calculations.

Yates, E. Carson, Jr.↗
NASA NTRS1992

An IDL-based analysis package for COBE and other skycube-formatted astronomical data

UIMAGE is a data analysis package written in IDL for the Cosmic Background Explorer (COBE) project. COBE has extraordinarily stringent accuracy requirements: 1 percent mid-infrared absolute photometry, 0.01 percent submillimeter absolute spectrometry, and 0.0001 percent submillimeter relative photometry. Thus, many of the transformations and image enhancements common to analysis of large data sets must be done with special care. UIMAGE is unusual in this sense in that it performs as many of its operations as possible on the data in its native format and projection, which in the case of COBE is the quadrilateralized sphereical cube ('skycube'). That is, after reprojecting the data, e.g., onto an Aitoff map, the user who performs an operation such as taking a crosscut or extracting data from a pixel is transparently acting upon the skycube data from which the projection was made, thereby preserving the accuracy of the result. Current plans call for formatting external data bases such as CO maps into the skycube format with a high-accuracy transformation, thereby allowing Guest Investigators to use UIMAGE for direct comparison of the COBE maps with those at other wavelengths from other instruments. It is completely menu-driven so that its use requires no knowledge of IDL. Its functionality includes I/O from the COBE archives, FITS files, and IDL save sets as well as standard analysis operations such as smoothing, reprojection, zooming, statistics of areas, spectral analysis, etc. One of UIMAGE's more advanced and attractive features is its terminal independence. Most of the operations (e.g., menu-item selection or pixel selection) that are driven by the mouse on an X-windows terminal are also available using arrow keys and keyboard entry (e.g., pixel coordinates) on VT200 and Tektronix-class terminals. Even limited grey scales of images are available this way. Obviously, image processing is very limited on this type of terminal, but it is nonetheless surprising how much analysis can be done on that medium. Such flexibility has the virtue of expanding the user community to those who must work remotely on non-image terminals, e.g., via modem.

Ewing, J. A.↗
NASA NTRS1994

Spectropolarimetry of hot, luminous stars

I review polarimetric observations of presumably single, hot luminous stars. The stellar types discussed are OB stars. B(e) supergiants, Luminous Blue Variables (LBV), Wolf-Rayet (W-R) stars, and type II supernovae (SN). It is shown that variable, intrinsic polarization is a common phenomenon in that part of the Hertzsprung-Russell (HR) diagram which these stars occupy. However, much observational work remains to be done before we can answer the most basic, statistical questions about the polarimetric properties of different groups of hot, luminous stars. Insight into the diagnostic power of polarization observations has been gained, but cannot be exploited without detailed models. Thus, while polarimetric observations do tell us that the mass-loss processes of all types of massive stars are time-dependent and anisotropic, the significance that this might have for the accuracy of their stellar parameters and evolutionary paths remains elusive.

Schulte-Ladbeck, Regina E.↗
NASA NTRS2003

Mathematical Inversion of Lightning Data: Techniques and Applications

A survey of some interesting mathematical inversion studies dealing with radio, optical, and electrostatic measurements of lightning are presented. A discussion of why NASA is interested in lightning, what specific physical properties of lightning are retrieved, and what mathematical techniques are used to perform the retrievals are discussed. In particular, a relatively new multi-station VHF time-of-arrival (TOA) antenna network is now on-line in Northern Alabama and will be discussed. The network, called the Lightning Mapping Array (LMA), employs GPS timing and detects VHF radiation from discrete segments (effectively point emitters) that comprise the channel of lightning strokes within cloud and ground flashes. The LMA supports on-going ground-validation activities of the low Earth orbiting Lightning Imaging Sensor (LIS) satellite developed at NASA Marshall Space Flight Center (MSFC) in Huntsville, Alabama. The LMA also provides detailed studies of the distribution and evolution of thunderstorms and lightning in the Tennessee Valley, and offers interesting comparisons with other meteorological/geophysical datasets. In order to take full advantage of these benefits, it is essential that the LMA channel mapping accuracy (in both space and time) be fully characterized and optimized. A new channel mapping retrieval algorithm is introduced for this purpose. To characterize the spatial distribution of retrieval errors, the algorithm has been applied to analyze literally tens of millions of computer-simulated lightning VHF point sources that have been placed at various ranges, azimuths, and altitudes relative to the LMA network. Statistical results are conveniently summarized in high-resolution, color-coded, error maps.

Koshak, William↗
NASA NTRS2007

A Comparison of Two Balance Calibration Model Building Methods

Simulated strain-gage balance calibration data is used to compare the accuracy of two balance calibration model building methods for different noise environments and calibration experiment designs. The first building method obtains a math model for the analysis of balance calibration data after applying a candidate math model search algorithm to the calibration data set. The second building method uses stepwise regression analysis in order to construct a model for the analysis. Four balance calibration data sets were simulated in order to compare the accuracy of the two math model building methods. The simulated data sets were prepared using the traditional One Factor At a Time (OFAT) technique and the Modern Design of Experiments (MDOE) approach. Random and systematic errors were introduced in the simulated calibration data sets in order to study their influence on the math model building methods. Residuals of the fitted calibration responses and other statistical metrics were compared in order to evaluate the calibration models developed with different combinations of noise environment, experiment design, and model building method. Overall, predicted math models and residuals of both math model building methods show very good agreement. Significant differences in model quality were attributable to noise environment, experiment design, and their interaction. Generally, the addition of systematic error significantly degraded the quality of calibration models developed from OFAT data by either method, but MDOE experiment designs were more robust with respect to the introduction of a systematic component of the unexplained variance.

DeLoach, Richard↗
NASA NTRS2009

An Algorithm for Obtaining the Distribution of 1-Meter Lightning Channel Segment Altitudes for Application in Lightning NOx Production Estimation

An algorithm has been developed to estimate the altitude distribution of one-meter lightning channel segments. The algorithm is required as part of a broader objective that involves improving the lightning NOx emission inventories of both regional air quality and global chemistry/climate models. The algorithm was tested and applied to VHF signals detected by the North Alabama Lightning Mapping Array (NALMA). The accuracy of the algorithm was characterized by comparing algorithm output to the plots of individual discharges whose lengths were computed by hand; VHF source amplitude thresholding and smoothing were applied to optimize results. Several thousands of lightning flashes within 120 km of the NALMA network centroid were gathered from all four seasons, and were analyzed by the algorithm. The mean, standard deviation, and median statistics were obtained for all the flashes, the ground flashes, and the cloud flashes. One-meter channel segment altitude distributions were also obtained for the different seasons.

Peterson, Harold↗
NASA NTRS2015

Estimation of Crop Gross Primary Production (GPP): Do Scaled (MODIS) Vegetation Indices Improve Performance? - 2

Satellite remote sensing estimates of Gross Primary Production (GPP) have routinely been made using spectral Vegetation Indices (VIs) over the past two decades. The Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), the green band Wide Dynamic Range Vegetation Index (WDRVIgreen), and the green band Chlorophyll Index (CIgreen) have been employed to estimate GPP under the assumption that GPP is proportional to the product of VI and photosynthetically active radiation (PAR) (where VI is one of four VIs: NDVI, EVI, WDRVIgreen, or CIgreen). However, the empirical regressions between VI*PAR and GPP measured locally at flux towers do not pass through the origin (i.e., the zero X-Y value for regressions). Therefore they are somewhat difficult to interpret and apply. This study investigates (1) what are the scaling factors and offsets (i.e., regression slopes and intercepts) between the fraction of PAR absorbed by chlorophyll of a canopy (fAPARchl) and the VIs, and (2) whether the scaled VIs developed in (1) can eliminate the deficiency and improve the accuracy of GPP estimates. Three AmeriFlux maize and soybean fields were selected for this study, two of which are irrigated and one is rainfed. The four VIs and fAPARchl of the fields were computed with the MODerate resolution Imaging Spectroradiometer (MODIS) satellite images. The GPP estimation performance for the scaled VIs was compared to results obtained with the original VIs and evaluated with standard statistics: the coefficient of determination (R2), the root mean square error (RMSE), and the coefficient of variation (CV). Overall, the scaled EVI obtained the best performance. The performance of the scaled NDVI, EVI and WDRVIgreen was improved across sites, crop types and soil/background wetness conditions. The scaled CIgreen did not improve results, compared to the original CIgreen. The scaled green band indices (WDRVIgreen, CIgreen) did not exhibit superior performance to either the scaled EVI or NDVI in estimating crop daily GPP at these agricultural fields. The scaled VIs are more physiologically meaningful than original un-scaled VIs, but scaling factors and offsets may vary across crop types and surface conditions.

Vegetation Index↗
NASA NTRS2018

The Use of Gridded Fossil Fuel CO2 Emissions (FFCO2) Inventory for Climate Mitigation Applications: Errors, Uncertainties, and Current and Future Challenges

Emission Inventory (EI) is a fundamental tool to monitor global compliance of greenhouse gases (GHGs) emissions reduction actions. Inventory guidelines provide a best practice to help EI compilers to make comparable national emission estimates, in spite of the differences in data availability across countries and regions. There are a variety of sources of errors and uncertainties, however, that originate beyond what the inventory guidelines define. For example, spatially-explicit EIs, which are a key product for atmospheric modeling applications, are often developed for research purposes, and there are no specific guidelines to disaggregate emission estimates from country scale. On top of that, EIs are fundamentally prone to systematic biases due to the simple calculation methodology and thus an objective evaluation (e.g. atmospheric top-down estimates) is needed to assure the accuracy of the estimates. ODIAC is a global high-resolution (1x1 km) fossil fuel carbon dioxide (CO2) gridded EI that is now often used in atmospheric CO2 modeling. ODIAC is based on disaggregation of national emission estimates made by CDIAC, which is the well accepted standard in the community. The ODIAC emission data product is updated on an annual basis using best available statistical data. Subnational spatial emission patterns are estimated using power plant profiles and satellite-observations of nighttime lights. In addition to the conventional CDIAC gridded data product, ODIAC carries international bunker emissions (shipping and aviation), which allows flux inversion modelers to accurately impose the global total fossil fuel emissions and their horizontal and vertical distribution. We have extensively evaluated ODIAC emissions using fine-grained EIs as well as a high-resolution atmospheric model simulation across different scales (national, subnational/regional, and urban policy relevant) with a focus on the uncertainties associated with the emission disaggregation. We have examined the use of NASA's Black Marble Suomi-NPP/VIIRS nightlight data.

Oda, Tomohiro↗
NASA NTRS1976

A demonstration of a transportable radio interferometric surveying system with 3-cm accuracy on a 307-m base line

A precision geodetic measurement system (Aries, for Astronomical Radio Interferometric Earth Surveying) based on the technique of very long base line interferometry has been designed and implemented through the use of a 9-m transportable antenna and the NASA 64-m antenna of the Deep Space Communications Complex at Goldstone, California. A series of experiments designed to demonstrate the inherent accuracy of a transportable interferometer was performed on a 307-m base line during the period from December 1973 to June 1974. This short base line was chosen in order to obtain a comparison with a conventional survey with a few-centimeter accuracy and to minimize Aries errors due to transmission media effects, source locations, and earth orientation parameters. The base-line vector derived from a weighted average of the measurements, representing approximately 24 h of data, possessed a formal uncertainty of about 3 cm in all components. This average interferometry base-line vector was in good agreement with the conventional survey vector within the statistical range allowed by the combined uncertainties (3-4 cm) of the two techniques.

Ong, K. M.↗
NASA NTRS1983

Estimates of the seasonal mean vertical velocity fields of the extratropical Northern Hemisphere

Indirect methods are employed to estimate the wintertime and summertime mean vertical velocity fields of the extratropical Northern Hemisphere and intercomparisons are made, together with comparisons with mean seasonal patterns of cloudiness and precipitation. Twice-daily NMC operational analyses produced general circulation statistics for 11 winters and 12 summers, permitting calculation of the seasonal NMC averages for 6 hr forecasts, solution of the omega equation, integration of continuity equation downward from 100 mb, and solution of the thermodynamic energy equation in the absence of diabatic heating. The methods all yielded similar vertical velocity patterns; however, the magnitude of the vertical velocities could not be calculated with great accuracy. Orography was concluded to have less of an effect in summer than in winter, when winds are stronger.

White, G. H.↗
NASA NTRS1987

Analyses and assessments of span wise gust gradient data from NASA B-57B aircraft

Analysis of turbulence measured across the airfoil of a Cambera B-57 aircraft is reported. The aircraft is instrumented with probes for measuring wind at both wing tips and at the nose. Statistical properties of the turbulence are reported. These consist of the standard deviations of turbulence measured by each individual probe, standard deviations and probability distribution of differences in turbulence measured between probes and auto- and two-point spatial correlations and spectra. Procedures associated with calculations of two-point spatial correlations and spectra utilizing data were addressed. Methods and correction procedures for assuring the accuracy of aircraft measured winds are also described. Results are found, in general, to agree with correlations existing in the literature. The velocity spatial differences fit a Gaussian/Bessel type probability distribution. The turbulence agrees with the von Karman turbulence correlation and with two-point spatial correlations developed from the von Karman correlation.

Frost, Walter↗
NASA NTRS2010

Advances in Landslide Hazard Forecasting: Evaluation of Global and Regional Modeling Approach

A prototype global satellite-based landslide hazard algorithm has been developed to identify areas that exhibit a high potential for landslide activity by combining a calculation of landslide susceptibility with satellite-derived rainfall estimates. A recent evaluation of this algorithm framework found that while this tool represents an important first step in larger-scale landslide forecasting efforts, it requires several modifications before it can be fully realized as an operational tool. The evaluation finds that the landslide forecasting may be more feasible at a regional scale. This study draws upon a prior work's recommendations to develop a new approach for considering landslide susceptibility and forecasting at the regional scale. This case study uses a database of landslides triggered by Hurricane Mitch in 1998 over four countries in Central America: Guatemala, Honduras, EI Salvador and Nicaragua. A regional susceptibility map is calculated from satellite and surface datasets using a statistical methodology. The susceptibility map is tested with a regional rainfall intensity-duration triggering relationship and results are compared to global algorithm framework for the Hurricane Mitch event. The statistical results suggest that this regional investigation provides one plausible way to approach some of the data and resolution issues identified in the global assessment, providing more realistic landslide forecasts for this case study. Evaluation of landslide hazards for this extreme event helps to identify several potential improvements of the algorithm framework, but also highlights several remaining challenges for the algorithm assessment, transferability and performance accuracy. Evaluation challenges include representation errors from comparing susceptibility maps of different spatial resolutions, biases in event-based landslide inventory data, and limited nonlandslide event data for more comprehensive evaluation. Additional factors that may improve algorithm performance accuracy include incorporating additional triggering factors such as tectonic activity, anthropogenic impacts and soil moisture into the algorithm calculation. Despite these limitations, the methodology presented in this regional evaluation is both straightforward to calculate and easy to interpret, making results transferable between regions and allowing findings to be placed within an inter-comparison framework. The regional algorithm scenario represents an important step in advancing regional and global-scale landslide hazard assessment and forecasting.

Kirschbaum, Dalia B.↗
NASA NTRS2021

Hybrid phenology matching model for robust crop phenological retrieval

Crop phenology regulates seasonal agroecosystem carbon, water, and energy exchanges, and is a key component in empirical and process-based crop models for simulating biogeochemical cycles of farmlands, assessing gross and net primary production, and forecasting the crop yield. The advances in phenology matching models provide a feasible means to monitor crop phenological progress using remote sensing observations, with a priori information of reference shapes and reference phenological transition dates. Yet the underlying geometrical scaling assumption of models, together with the challenge in defining phenological references, hinders the applicability of phenology matching in crop phenological studies. The objective of this study is to develop a novel hybrid phenology matching model to robustly retrieve a diverse spectrum of crop phenological stages using satellite time series. The devised hybrid model leverages the complementary strengths of phenometric extraction methods and phenology matching models. It relaxes the geometrical scaling assumption and can characterize key phenological stages of crop cycles, ranging from farming practice-relevant stages (e.g., planted and harvested) to crop development stages (e.g., emerged and mature). To systematically evaluate the influence of phenological references on phenology matching, four representative phenological reference scenarios under varying levels of phenological calibrations in terms of time and space are further designed with publicly accessible phenological information. The results indicate that the hybrid phenology matching model can achieve high accuracies for estimating corn and soybean phenological growth stages in Illinois, particularly with the year- and region-adjusted phenological reference (R-squared higher than 0.9 and RMSE less than 5 days for most phenological stages). The inter-annual and regional phenological patterns characterized by the hybrid model correspond well with those in the crop progress reports (CPRs) from the USDA National Agricultural Statistics Service (NASS). Compared to the benchmark phenology matching model, the hybrid model is more robust to the decreasing levels of phenological reference calibrations, and is particularly advantageous in retrieving crop early phenological stages (e.g., planted and emerged stages) when the phenological reference information is limited. This innovative hybrid phenology matching model, together with CPR-enabled phenological reference calibrations, holds 3 considerable promise in revealing spatio-temporal patterns of crop phenology over extended geographical regions.

Phenology↗
NASA NTRSDate not supplied

Interpretable Machine Learning Models for Autonomous Characterization of Analogue Ocean World Seawater Chemistry and Biosignature Potential Using Isotope Ratio Data

Background: Future missions to ocean worlds, such as Enceladus and Europa, will attempt to characterize the subsurface seawater chemistry and assess the potential for life. Such missions will be equipped with capabilities to precisely measure volatile isotopes in plumes, atmospheres, and exospheres. Motivation: While large isotopic fractionations can indicate a biological source, there are signatures resulting from abiotic geochemical processes that mimic isotopic biosignatures. While machine learning (ML) has the potential to disentangle competing effects and biotic mimicry, high-dimensional isotope ratio mass spectrometry (IRMS) data is likely to contain noise/irrelevant features and involve complex statistical interactions that make human inference and interpretation difficult. Further, ML predictions with as far-reaching implications as an extraterrestrial biosignature on an ocean world requires the use of interpretable models (i.e., not “black box” models) with physically and mathematically meaningful feature spaces along with false positive diagnostics. Methods: We use volatile CO2 IRMS data of analogue ocean world seawaters to validate an ML approach to provide biogeochemical context for biosignature detection. We employ a feature selection method called nearest-neighbor projected distance regression (NPDR) that detects statistical interactions and helps elucidate the mechanisms of the Random Forest classification models. Results: We train and validate predictive ML models on volatile CO2 IRMS data of analogue ocean world seawaters to predict major salt components (e.g., MgSO4, NaHCO3), pH, ionic strength, and the presence of biosignatures. Features derived from IRMS measurements are augmented with extracted time-series features. Our results show high test accuracy and interpretability, which is increased by interaction network visualization, sample-wise variable importance scores, and single-sample class probability estimates. We demonstrate an ML mission software solution that triggers autonomous data transmission and biogeochemical sample prediction.

geochemistry↗
NASA NTRS2010

Situational Lightning Climatologies

Research has revealed distinct spatial and temporal distributions of lightning occurrence that are strongly influenced by large-scale atmospheric flow regimes. It was believed there were two flow systems, but it has been discovered that actually there are seven distinct flow regimes. The Applied Meteorology Unit (AMU) has recalculated the lightning climatologies for the Shuttle Landing Facility (SLF), and the eight airfields in the National Weather Service in Melbourne (NWS MLB) County Warning Area (CWA) using individual lightning strike data to improve the accuracy of the climatologies. The software determines the location of each CG lightning strike with 5-, 10-, 20-, and 30-nmi (.9.3-, 18.5-, 37-, 55.6-km) radii from each airfield. Each CG lightning strike is binned at 1-, 3-, and 6-hour intervals at each specified radius. The software merges the CG lightning strike time intervals and distance with each wind flow regime and creates probability statistics for each time interval, radii, and flow regime, and stratifies them by month and warm season. The AMU also updated the graphical user interface (GUI) with the new data.

Bauman, William↗
NASA NTRS2012

Spatial Distribution of Accuracy of Aerosol Retrievals from Multiple Satellite Sensors

Remote sensing of aerosols from space has been a subject of extensive research, with multiple sensors retrieving aerosol properties globally on a daily or weekly basis. The diverse algorithms used for these retrievals operate on different types of reflected signals based on different assumptions about the underlying physical phenomena. Depending on the actual retrieval conditions and especially on the geographical location of the sensed aerosol parcels, the combination of these factors might be advantageous for one or more of the sensors and unfavorable for others, resulting in disagreements between similar aerosol parameters retrieved from different sensors. In this presentation, we will demonstrate the use of the Multi-sensor Aerosol Products Sampling System (MAPSS) to analyze and intercompare aerosol retrievals from multiple spaceborne sensors, including MODIS (on Terra and Aqua), MISR, OMI, POLDER, CALIOP, and SeaWiFS. Based on this intercomparison, we are determining geographical locations where these products provide the greatest accuracy of the retrievals and identifying the products that are the most suitable for retrieval at these locations. The analyses are performed by comparing quality-screened satellite aerosol products to available collocated ground-based aerosol observations from the Aerosol Robotic Network (AERONET) stations, during the period of 2006-2010 when all the satellite sensors were operating concurrently. Furthermore, we will discuss results of a statistical approach that is applied to the collocated data to detect and remove potential data outliers that can bias the results of the analysis.

Petrenko, Maksym↗